[Hiring] Data & Analytics Engineer @CI&T

Role Description

We are looking for a Data & Analytics Engineer supporting an AI/ML implementation for demand forecasting and resource optimization in the public transportation / fare collection industry. Works alongside an AWS ProServe ML Specialist on EDA, feature engineering, capacity modeling, and operational dashboards.

Responsibilities:

• Exploratory Data Analysis (EDA):
  • Conduct EDA and statistical profiling to identify trends and insights from data.
  • Perform feature engineering specifically for time-series forecasting.
• Data Wrangling and Preparation:
  • Extract and transform data from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats.
  • Develop pipelines for data ingestion and processing.
• Machine Learning Modeling:
  • Build classical ML models for time-series forecasting, regression, and capacity/throughput modeling.
  • Evaluate model performance using metrics such as RMSE, MAE, and MAPE, documenting performance results.
• Data Visualization:
  • Create insightful data visualizations and dashboards using Amazon QuickSight or equivalent BI tools.
• Python Data Stack:
  • Utilize the Python data stack (pandas, NumPy, scikit-learn, matplotlib/seaborn) for data manipulation and analysis.
• Model Explainability:
  • Apply SHAP or other model explainability techniques to interpret model outputs.
• Collaboration and Communication:
  • Work closely with stakeholders to translate business rules into effective feature engineering pipelines.
  • Engage in milestone-driven, Firm Fixed Price delivery models, ensuring timely project completion.

Qualifications

• 4+ years in data engineering or applied data science roles, preferably with experience on AWS.
• Proficient in exploratory data analysis (EDA), statistical profiling, and feature engineering for time-series forecasting.
• Experience in data wrangling from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats.
• Strong understanding of classical ML modeling techniques, including time-series forecasting and regression.
• Familiarity with model evaluation metrics (RMSE, MAE, MAPE) and performance documentation.
• Experience in data visualization and dashboard development using Amazon QuickSight or equivalent BI tools.
• Hands-on experience with Amazon SageMaker (training, evaluation, Clarify).
• Proficient in the Python data stack, including pandas, NumPy, scikit-learn, matplotlib, and seaborn.
• Working knowledge of SQL and dimensional modeling.
• Familiarity with SHAP or model explainability techniques is a plus.

Requirements

• AWS Certified Cloud Practitioner
• AWS Certified Data Engineer – Associate
• AWS Certified Machine Learning – Associate or AWS Certified Machine Learning – Specialty

Benefits

• Premium Healthcare
• Meal voucher
• Maternity and Parental leaves
• Mobile services subsidy
• Sick pay-Life insurance
• CI&T University
• Colombian Holidays
• Paid Vacations
• And many others.